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Update flywire_googledrive.R
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@alexanderbates
alexanderbates committed Dec 31, 2023
1 parent 94532ef commit 881b4ed
Showing 1 changed file with 184 additions and 1 deletion.
185 changes: 184 additions & 1 deletion R/flywire_googledrive.R
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Original file line number Diff line number Diff line change
Expand Up @@ -91,6 +91,7 @@
flywire_neurons <- function(x = NULL,
WithConnectors = FALSE,
local = FALSE,
version = NULL,
brain = c("FlyWire", "JRCFIB2018Fraw","JRCFIB2018F","FAFB","FAFB14","JFRC2", "JFRC2013","JRC2018F","FCWB"),
mirror = FALSE,
type = c("neurons", "swc","dotprops","cut_dotprops"),
Expand All @@ -115,7 +116,11 @@ flywire_neurons <- function(x = NULL,
# Get Google drive folder
savedir = good_savedir(local = local)
neuronsdir = file.path(savedir,"flywire_neurons/")
fhdir = file.path(neuronsdir,brain,"/")
if(!is.null(version)){
fhdir = file.path(neuronsdir,version,brain,"/")
}else{
fhdir = file.path(neuronsdir,brain,"/")
}

# Get synapses from private drive
if(type%in%c("dotprops","cut_dotprops")){
Expand Down Expand Up @@ -1090,3 +1095,181 @@ matches_update <- function(matching_sheet = options()$hemibrainr_matching_gsheet
}


# flywire read swc files
flywire_read_swc <- function(swc,
meta = NULL,
ids = NULL,
id = 'root_id',
template = "Flywire",
nams = NULL){
if(!is.null(ids)){
fw.skels <- nat::read.neurons(swc,
pattern = paste(ids,collapse="|"),
OmitFailures = TRUE)
}else{
fw.skels <- nat::read.neurons(swc,
OmitFailures = TRUE)
}
if(is.null(nams)){
fw.skels <- fw.skels[!duplicated(names(fw.skels))]
attr(fw.skels,"df") <- data.frame(root_id=names(fw.skels))
}else{
new.nams <- nams[names(fw.skels)]
new.nams[is.na(new.nams)] = names(fw.skels)[is.na(new.nams)]
fw.skels <- fw.skels[!duplicated(new.nams)]
attr(fw.skels,"df") <- data.frame(root_id=new.nams)
}
fw.skels[,"dataset"] = "flywire"
nat.templatebrains::regtemplate(fw.skels) = regtemplate
if(!is.null(meta)){
meta <- meta[!duplicated(meta$root_id),]
fw.skels <- hemibrainr:::update_metdata(fw.skels, meta = meta, id = id)
}
fw.skels
}

flywire_read_synapse_csvs <- function(save.path,
prepost = NULL,
numCores = NULL,
process = TRUE,
flywire.cleft.threshold = 50,
nt.cols = c("gaba", "acetylcholine", "glutamate",
"octopamine", "serotonin", "dopamine",
"neither")){
if(!is.null(numCores)){
cl <- parallel::makeCluster(2L)
}else{
cl = NULL
}
files <- list.files(save.path, full.names = TRUE)
message("Reading synapses: ")
synapse.csvs <- pbapply::pblapply(files, function(file){
root_id <- gsub("\\.csv","",basename(file))
csv <- try(as.data.frame(suppressMessages(readr::read_csv(file, col_types = hemibrainr:::sql_col_types))))
if(is.data.frame(csv)){
if(nrow(csv)){
csv$root_id <- root_id
if(process){
csv <- flywire_process_synapses(csv,
prepost=prepost,
flywire.cleft.threshold = flywire.cleft.threshold,
nt.cols = nt.cols)
csv$treenode_id <- NULL
}else{
csv
}
}else{
NULL
}
}else{
NULL
}
},
cl = cl)
if(!is.null(cl)){
parallel::stopCluster(cl)
}
synapse.csvs <- synapse.csvs[sapply(synapse.csvs,is.data.frame)]
do.call(plyr::rbind.fill, synapse.csvs)
}

flywire_process_synapses <-function(fw.synapses,
prepost = NULL,
flywire.cleft.threshold = 50,
nt.cols = c("gaba", "acetylcholine", "glutamate", "octopamine", "serotonin", "dopamine", "neither")){
colnames(fw.synapses) <- snakecase::to_snake_case(colnames(fw.synapses))
key.cols <- c("offset", "connector_id", "treenode_id", "x", "y", "z", "scores", "cleft_scores",
"syn_top_p", "syn_top_nt", "gaba", "acetylcholine", "glutamate",
"octopamine", "serotonin", "dopamine", "prepost", "pre_id", "post_id",
"inside", "strahler_order", "label", "geodesic_distance", "geodesic_distance_norm")
fw.synapses <- fw.synapses[,!duplicated(colnames(fw.synapses))]
fw.synapses <- fw.synapses %>%
dplyr::rename(syn_top_p = top_p,
syn_top_nt = top_nt)
missin.cols <- setdiff(key.cols,colnames(fw.synapses))
for(m in missin.cols){
warning("missing synapse column: ", m, " for rootid: ", fw.synapses$root_id[[1]])
fw.synapses[[m]] <- NA
}
if(!all(key.cols%in%colnames(fw.synapses))){
warning("not all column names found, dropping a synapse list")
return(NULL)
}
fw.synapses = fw.synapses %>%
dplyr::filter(cleft_scores>flywire.cleft.threshold,
pre_id != post_id) %>%
dplyr::select(c(offset, connector_id, treenode_id,
x, y, z,
scores, cleft_scores,
syn_top_p, syn_top_nt,
gaba, acetylcholine, glutamate, octopamine, serotonin, dopamine,
prepost,
#segmentid_pre, segmentid_post,
#pre_svid, post_svid,
pre_id, post_id,
inside, strahler_order, label,
geodesic_distance, geodesic_distance_norm
)) %>%
dplyr::mutate(label = hemibrainr:::standard_compartments(label)) %>%
dplyr::group_by(pre_id, post_id, prepost, label) %>%
dplyr::mutate(count = dplyr::n(),
geodesic_distance = as.numeric(geodesic_distance),
geodesic_distance_norm = as.numeric(geodesic_distance_norm)
)%>%
dplyr::ungroup() %>%
as.data.frame(stringsAsFactors = FALSE)
if(!is.null(prepost)){
if(prepost==0){
fw.synapses <- fw.synapses %>%
dplyr::filter(prepost==0) %>%
dplyr::rowwise() %>%
dplyr::mutate(syn_top_nt = nt.cols[which.max(c(gaba, acetylcholine, glutamate, octopamine, serotonin, dopamine))]) %>%
dplyr::mutate(syn_top_p = max(c(gaba, acetylcholine, glutamate, octopamine, serotonin, dopamine))) %>%
dplyr::ungroup()
}else{
fw.synapses <- fw.synapses %>%
dplyr::filter(prepost==1) %>%
dplyr::rowwise() %>%
dplyr::mutate(syn_top_nt = nt.cols[which.max(c(gaba, acetylcholine, glutamate, octopamine, serotonin, dopamine))]) %>%
dplyr::mutate(syn_top_p = max(c(gaba, acetylcholine, glutamate, octopamine, serotonin, dopamine))) %>%
dplyr::ungroup()
}
}
fw.synapses <- round_dataframe(fw.synapses, digits = 4)
fw.synapses
}

flywire_read_metrics_csvs <- function(save.path){
files <- list.files(save.path, full.names = TRUE)
message("Reading metrics: ")
metrics.csvs <- pbapply::pblapply(files, function(file){
root_id <- gsub("\\.csv","",basename(file))
csv <- try(suppressMessages(readr::read_csv(file, col_types = hemibrainr:::sql_col_types)))
csv
})
metrics.csvs <- metrics.csvs[sapply(metrics.csvs,is.data.frame)]
do.call(plyr::rbind.fill, metrics.csvs)
}

flywire_read_swc_split <-function(swc, synapses, meta, ids = NULL, regtemplate = "Flywire"){
message("Reading skeletons: ")
fw.skels <- flywire_read_swc(swc = swc,
ids = ids,
meta = fw.meta)
pb <- progress::progress_bar$new(total = length(fw.skels))
message("reading synapses: ")
for(id in names(fw.skels)){
pb$tick()
file <- file.path(synapses,paste0(id,".csv"))
csv <- suppressMessages(readr::read_csv(file, col_types = hemibrainr:::sql_col_types))
csv <- flywire_process_synapses(csv)
fw.skels[match(id,names(fw.skels))][[1]]$connectors <- csv
}
fw.skels <- nat::nlapply(fw.skels, function(neuron){
class(neuron) <- c("catmaidneuron","neuprintneuron","neuron")
neuron
})
fw.skels
}


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